Abstract
Rheumatoid arthritis (RA) is a chronic autoimmune disorder of bone joints caused by the complex interplay between several factors like body physiology, the environment with genetic background. The recent meta-analysis of GWAS has expanded the total number of RA-associated loci to more than 100, out of which approximately similar to 97% (98 variants) loci are located in non-coding regions, and the other similar to 3% (3 variants) are in three different non-HLA genes, i.e., TYK2 (Prp1104Ala), IL6R (Asp358Ala), and PTPN22 (Trp620Arg). However, whether these variants prompt changes in the protein phenotype with regards to its stability, structure, and interaction with other molecules, remains unknown. Thus, we selected the three clinically pathogenic variants described above, as positive controls and applied diverse computational methods to scrutinize if those mutations cause changes in the protein phenotype. Both wild type and mutant protein structures of PTPN22 (W620R), IL6R (D358A), and TYK2 (P1104A) were modeled and studied for structural deviations. Furthermore, we have also studied the secondary structure characteristics, solvent accessibility and stability, and the molecular interaction deformities caused by the amino acid substitutions. We observed that simple nucleotide predictions of SIFT, PolyPhen, CADD and FATHMM yields mixed findings in screening the RA-missense variants which showed a >= P-value threshold of 5 x 10(-8) in genome wide association studies. However, structure-based analysis confirms that mutant structures shows subtle but significant changes at their core regions, but their functional domains seems to lose wild type like functional interaction. Our findings suggest that the multidirectional computational analysis of clinically potential RA-mutations could act as a primary screening step before undertaking functional biology assays.